PROJECT SUMMARY/ABSTRACT The ability of tumor cells to evade the immune system is a well-known, yet poorly understood phenomenon in early cancer development. Despite promising immunotherapy strategies that have emerged from targeting these interactions, there is relatively little known about the complete repertoire of receptor-ligand interactions that contribute to immune evasion. We seek to understand how glycosylation, a well-established aberrant modification in cancer, aids cancer cells in evading the immune system. Identification of glycoproteins that modulate immune function could lead to new types of therpaies and could also serve as companion diagnostic biomarkers to guide patient selection of immunotherapies at an early time point in prostate cancer and clear cell renal cell carcinoma. First, because sialic acid is known to be overexpressed on the surface of cancer cells, we will use intact glycoproteomics methods developed in-house to enrich and identify sialoglycoproteins from cancerous and matched healthy tissues from patients. Quantitative comparative analyses will reveal changes in sialoglycoprotein expression and illuminate candidate ligands for sialic acid-binding proteins in the tumor microenvironment that potentially contribute to immune inactivation. Correlation of these glycoproteomic datasets with RNA-seq data focused on glycogene expression will bolster the assignment of specific glycoforms as cancer biomarkers. Second, using immunohistochemistry and CODEX methods, we will analyze expression levels of sialic acid-binding immunoglobulin-type lectin (Siglec) receptor proteins on tumor- resident immune cells and cross-correlate the findings with RNA-seq data as well as immune cell markers. We will also probe for the presence of ligands for various Siglec isoforms on tumor cell surfaces and obtain spatial information about their distribution on immune cells in intact tumor tissue. For any Siglecs identified as prominently displayed on immune cells in the tumor environment, we will develop cell-based assays to probe their contribution to tumor cell immunoreactivity. Third, we will perform a genome-wide screening using CRISPRi to identify genes that facilitate the binding of Siglecs to cancer cells. Finally, we will correlate the datasets from Aims 1, 2, and 3 with patient outcomes in a larger set of tissue samples contained on a tissue microarray, and evaluate their utility as prognostic indicators.